metadata
library_name: peft
tags:
- generated_from_trainer
base_model: NousResearch/Llama-2-7b-hf
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: llama-2-ner
results: []
llama-2-ner
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1250
- Precision: 0.5365
- Recall: 0.5421
- F1: 0.5393
- Accuracy: 0.9778
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0009
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 39 | 0.1314 | 0.3137 | 0.0842 | 0.1328 | 0.9676 |
| No log | 2.0 | 78 | 0.1068 | 0.2567 | 0.3526 | 0.2971 | 0.9669 |
| No log | 3.0 | 117 | 0.0806 | 0.3886 | 0.3579 | 0.3726 | 0.9736 |
| No log | 4.0 | 156 | 0.0710 | 0.4455 | 0.5158 | 0.4780 | 0.9757 |
| No log | 5.0 | 195 | 0.0852 | 0.5217 | 0.4421 | 0.4786 | 0.9758 |
| No log | 6.0 | 234 | 0.1035 | 0.5179 | 0.5316 | 0.5247 | 0.9773 |
| No log | 7.0 | 273 | 0.1237 | 0.5344 | 0.5316 | 0.5330 | 0.9773 |
| No log | 8.0 | 312 | 0.1250 | 0.5365 | 0.5421 | 0.5393 | 0.9778 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1